This map presents the mean relative humidity between about 3000 and 6000m a.s.l. - equivalent to the atmospheric
layer between 10,000 and 20,000 ft. This is the atmospheric region where middle and high stratus clouds form.
They are typically fringing a warm ridge along the anticyclonic sector of a frontal zone. In general, middle and high
stratus clouds are a good indicator for the run of the jet stream. Mean Relative Humidity in the layer between about 600 and 3000 m above ground

GFS:

The Global Forecast System (GFS) is a global numerical weather prediction computer model run by NOAA. This mathematical model is run four times a day and produces forecasts up to 16 days in advance, but with decreasing spatial and temporal resolution over time it is widely accepted that beyond 7 days the forecast is very general and not very accurate.

The model is run in two parts: the first part has a higher resolution and goes out to 180 hours (7 days) in the future, the second part runs from 180 to 384 hours (16 days) at a lower resolution. The resolution of the model varies in each part of the model: horizontally, it divides the surface of the earth into 35 or 70 kilometre grid squares; vertically, it divides the atmosphere into 64 layers and temporally, it produces a forecast for every 3rd hour for the first 180 hours, after that they are produced for every 12th hour.

NWP:

Numerical weather prediction uses current weather conditions as input into mathematical models of the atmosphere to predict the weather. Although the first efforts to accomplish this were done in the 1920s, it wasn't until the advent of the computer and computer simulation that it was feasible to do in real-time. Manipulating the huge datasets and performing the complex calculations necessary to do this on a resolution fine enough to make the results useful requires the use of some of the most powerful supercomputers in the world. A number of forecast models, both global and regional in scale, are run to help create forecasts for nations worldwide. Use of model ensemble forecasts helps to define the forecast uncertainty and extend weather forecasting farther into the future than would otherwise be possible.